Druid is designed for workflows where fast ad-hoc analytics, instant data visibility, or supporting high concurrency is important. As such, Druid is often used to power UIs where an interactive, consistent user experience is desired.
Druid has been benchmarked to greatly outperform legacy solutions. Druid combines novel storage ideas, indexing structures, and both exact and approximate queries to return most results in under a second.
Druid streams data from message buses such as Apache Kafka, and Amazon Kinesis, and batch load files from data lakes such as HDFS, and Amazon S3. Druid supports most popular file formats for structured and semi-structured data.
Druid can be deployed in any *NIX environment on commodity hardware, both in the cloud and on premise. Deploying Druid is easy: scaling up and down is as simple as adding and removing Druid services.